Use case · GADS Cause Code Analysis

Find What's Driving Forced Outages

DOTA AI connects to GADS read-only and ranks the cause codes driving your forced outage hours, by unit, in minutes.

Explainer video in production

The interactive walkthrough for Find What's Driving Forced Outages is being produced. The full use case is below.

Illustrative data. No real utility names or plant names are used.

4,860 h
Forced outage hours
312
Forced outage events
6.4%
Fleet EFOR
Built for

Reliability engineers, plant managers, generation performance teams

The problem

The GADS event data is already there. But getting answers means exports, pivot tables, and another request in the IT queue.

With DOTA AI

DOTA AI connects to GADS read-only and ranks the cause codes driving your forced outage hours, by unit, in minutes.

How it works

From a question to a deployed app.

01

Ask

Your analyst asks in plain English: top 10 cause codes by forced outage hours, last 12 months, by unit.

02

Connect

GADS Events and the Cause Code Library snap in read-only, with the permissions you already have.

03

Analyze

DOTA ranks the causes, brackets the vital few, and drills into any unit and quarter.

04

Share

Save it as a live dashboard for plant managers and planners. It runs as software, the same way, every time.

What you see
  • The top 3 causes drive 52% of forced outage hours
  • Boiler tube leaks lead the fleet
  • Unit 3 tube leak hours up 2.4x in 12 months
  • Shared live dashboard, the same result every run
Source systems
GADSCMMSPI historian

The takeaway

Your data. Your rules. Your solution.

Build find what's driving forced outages on your data.

See DOTA AI build a real utility app on your data in a 30-minute working session.